{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import QUANTAXIS as QA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "AC=QA.QA_Account().from_message(QA.QA_fetch_account()[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "pr=QA.QA_Performance(AC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>amount</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>pnl_ratio</th>\n",
       "      <th>pnl_money</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>000001</th>\n",
       "      <td>2018-01-03 09:30:00</td>\n",
       "      <td>2018-01-02 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>13.53</td>\n",
       "      <td>13.70</td>\n",
       "      <td>-0.012409</td>\n",
       "      <td>-12.408759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000001</th>\n",
       "      <td>2018-01-29 09:30:00</td>\n",
       "      <td>2018-01-12 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>13.93</td>\n",
       "      <td>13.55</td>\n",
       "      <td>0.028044</td>\n",
       "      <td>28.044280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>2018-01-31 09:30:00</td>\n",
       "      <td>2018-01-24 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>20.73</td>\n",
       "      <td>22.08</td>\n",
       "      <td>-0.061141</td>\n",
       "      <td>-61.141304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600000</th>\n",
       "      <td>2018-02-02 09:30:00</td>\n",
       "      <td>2018-01-04 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>13.10</td>\n",
       "      <td>12.66</td>\n",
       "      <td>0.034755</td>\n",
       "      <td>34.755134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600000</th>\n",
       "      <td>2018-02-08 09:30:00</td>\n",
       "      <td>2018-02-05 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>13.18</td>\n",
       "      <td>13.49</td>\n",
       "      <td>-0.022980</td>\n",
       "      <td>-22.979985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>2018-03-19 09:30:00</td>\n",
       "      <td>2018-03-08 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>32.05</td>\n",
       "      <td>33.64</td>\n",
       "      <td>-0.047265</td>\n",
       "      <td>-47.265161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000001</th>\n",
       "      <td>2018-03-26 09:30:00</td>\n",
       "      <td>2018-03-08 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>11.03</td>\n",
       "      <td>12.11</td>\n",
       "      <td>-0.089182</td>\n",
       "      <td>-89.182494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>2018-04-02 09:30:00</td>\n",
       "      <td>2018-02-13 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>22.70</td>\n",
       "      <td>20.10</td>\n",
       "      <td>0.129353</td>\n",
       "      <td>129.353234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>2018-04-16 09:30:00</td>\n",
       "      <td>2018-03-29 15:00:00</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>30.39</td>\n",
       "      <td>34.16</td>\n",
       "      <td>-0.110363</td>\n",
       "      <td>-110.362998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  sell_date             buy_date  amount  sell_price  \\\n",
       "code                                                                   \n",
       "000001  2018-01-03 09:30:00  2018-01-02 15:00:00  1000.0       13.53   \n",
       "000001  2018-01-29 09:30:00  2018-01-12 15:00:00  1000.0       13.93   \n",
       "000004  2018-01-31 09:30:00  2018-01-24 15:00:00  1000.0       20.73   \n",
       "600000  2018-02-02 09:30:00  2018-01-04 15:00:00  1000.0       13.10   \n",
       "600000  2018-02-08 09:30:00  2018-02-05 15:00:00  1000.0       13.18   \n",
       "000002  2018-03-19 09:30:00  2018-03-08 15:00:00  1000.0       32.05   \n",
       "000001  2018-03-26 09:30:00  2018-03-08 15:00:00  1000.0       11.03   \n",
       "000004  2018-04-02 09:30:00  2018-02-13 15:00:00  1000.0       22.70   \n",
       "000002  2018-04-16 09:30:00  2018-03-29 15:00:00  1000.0       30.39   \n",
       "\n",
       "        buy_price  pnl_ratio   pnl_money  \n",
       "code                                      \n",
       "000001      13.70  -0.012409  -12.408759  \n",
       "000001      13.55   0.028044   28.044280  \n",
       "000004      22.08  -0.061141  -61.141304  \n",
       "600000      12.66   0.034755   34.755134  \n",
       "600000      13.49  -0.022980  -22.979985  \n",
       "000002      33.64  -0.047265  -47.265161  \n",
       "000001      12.11  -0.089182  -89.182494  \n",
       "000004      20.10   0.129353  129.353234  \n",
       "000002      34.16  -0.110363 -110.362998  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.pnl_fifo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.plot_pnlmoney(pr.pnl_fifo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.plot_pnlratio(pr.pnl_fifo)"
   ]
  }
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